Overview

Dataset statistics

Number of variables9
Number of observations458
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory33.2 KiB
Average record size in memory74.3 B

Variable types

Categorical2
Text4
DateTime2
Numeric1

Dataset

Description한국인터넷진흥원 대표홈페이지DB에 저장된 연구보고서정보입니다.
Author한국인터넷진흥원
URLhttps://www.data.go.kr/data/15092586/fileData.do

Alerts

등록번호 is highly skewed (γ1 = 21.39747367)Skewed
등록번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:04:59.585187
Analysis finished2023-12-12 13:05:00.661692
Duration1.08 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

분류
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
1
402 
0
56 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1 402
87.8%
0 56
 
12.2%

Length

2023-12-12T22:05:01.050201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:05:01.149310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 402
87.8%
0 56
 
12.2%

보고서명
Text

Distinct454
Distinct (%)99.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-12T22:05:01.503474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length96
Median length53
Mean length25.858079
Min length7

Characters and Unicode

Total characters11843
Distinct characters454
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique450 ?
Unique (%)98.3%

Sample

1st row2008 국내 정보보호산업 시장 및 동향조사
2nd row이동단말 환경에서 안전한 위치정보 제공을 위한 보안기술 개발
3rd row정보보호제품 품질 평가기준 연구
4th row정보보호산업 분류 및 실태 조사
5th row자바 보안 기술분석서
ValueCountFrequency (%)
연구 172
 
6.2%
및 120
 
4.3%
개발 55
 
2.0%
분석 51
 
1.8%
41
 
1.5%
정보보호 39
 
1.4%
위한 34
 
1.2%
방안 31
 
1.1%
관한 22
 
0.8%
조사 21
 
0.8%
Other values (1270) 2183
78.8%
2023-12-12T22:05:02.066371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2312
 
19.5%
보 410
 
3.5%
구 238
 
2.0%
정 231
 
2.0%
연 199
 
1.7%
인 173
 
1.5%
기 166
 
1.4%
서 158
 
1.3%
개 155
 
1.3%
안 147
 
1.2%
Other values (444) 7654
64.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8223
69.4%
Space Separator 2312
 
19.5%
Uppercase Letter 552
 
4.7%
Lowercase Letter 311
 
2.6%
Decimal Number 253
 
2.1%
Other Punctuation 75
 
0.6%
Dash Punctuation 44
 
0.4%
Close Punctuation 36
 
0.3%
Open Punctuation 35
 
0.3%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 410
 
5.0%
구 238
 
2.9%
정 231
 
2.8%
연 199
 
2.4%
인 173
 
2.1%
기 166
 
2.0%
서 158
 
1.9%
개 155
 
1.9%
안 147
 
1.8%
호 146
 
1.8%
Other values (370) 6200
75.4%
Uppercase Letter
ValueCountFrequency (%)
I 77
13.9%
S 63
11.4%
P 50
 
9.1%
T 48
 
8.7%
C 43
 
7.8%
D 41
 
7.4%
A 34
 
6.2%
E 31
 
5.6%
U 19
 
3.4%
N 18
 
3.3%
Other values (14) 128
23.2%
Lowercase Letter
ValueCountFrequency (%)
e 40
12.9%
o 36
11.6%
i 32
10.3%
r 24
 
7.7%
c 22
 
7.1%
a 22
 
7.1%
t 21
 
6.8%
n 19
 
6.1%
u 11
 
3.5%
v 11
 
3.5%
Other values (14) 73
23.5%
Decimal Number
ValueCountFrequency (%)
0 101
39.9%
2 51
20.2%
1 20
 
7.9%
9 20
 
7.9%
8 14
 
5.5%
3 14
 
5.5%
5 13
 
5.1%
6 11
 
4.3%
4 6
 
2.4%
7 3
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/ 17
22.7%
· 15
20.0%
, 14
18.7%
. 13
17.3%
: 12
16.0%
＆ 2
 
2.7%
？ 1
 
1.3%
* 1
 
1.3%
Close Punctuation
ValueCountFrequency (%)
) 35
97.2%
」 1
 
2.8%
Open Punctuation
ValueCountFrequency (%)
( 34
97.1%
「 1
 
2.9%
Space Separator
ValueCountFrequency (%)
2312
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8223
69.4%
Common 2757
 
23.3%
Latin 863
 
7.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 410
 
5.0%
구 238
 
2.9%
정 231
 
2.8%
연 199
 
2.4%
인 173
 
2.1%
기 166
 
2.0%
서 158
 
1.9%
개 155
 
1.9%
안 147
 
1.8%
호 146
 
1.8%
Other values (370) 6200
75.4%
Latin
ValueCountFrequency (%)
I 77
 
8.9%
S 63
 
7.3%
P 50
 
5.8%
T 48
 
5.6%
C 43
 
5.0%
D 41
 
4.8%
e 40
 
4.6%
o 36
 
4.2%
A 34
 
3.9%
i 32
 
3.7%
Other values (38) 399
46.2%
Common
ValueCountFrequency (%)
2312
83.9%
0 101
 
3.7%
2 51
 
1.8%
- 44
 
1.6%
) 35
 
1.3%
( 34
 
1.2%
1 20
 
0.7%
9 20
 
0.7%
/ 17
 
0.6%
· 15
 
0.5%
Other values (16) 108
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8220
69.4%
ASCII 3600
30.4%
None 20
 
0.2%
Compat Jamo 3
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2312
64.2%
0 101
 
2.8%
I 77
 
2.1%
S 63
 
1.8%
2 51
 
1.4%
P 50
 
1.4%
T 48
 
1.3%
- 44
 
1.2%
C 43
 
1.2%
D 41
 
1.1%
Other values (59) 770
 
21.4%
Hangul
ValueCountFrequency (%)
보 410
 
5.0%
구 238
 
2.9%
정 231
 
2.8%
연 199
 
2.4%
인 173
 
2.1%
기 166
 
2.0%
서 158
 
1.9%
개 155
 
1.9%
안 147
 
1.8%
호 146
 
1.8%
Other values (369) 6197
75.4%
None
ValueCountFrequency (%)
· 15
75.0%
＆ 2
 
10.0%
？ 1
 
5.0%
」 1
 
5.0%
「 1
 
5.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 3
100.0%

관리조직1
Categorical

Distinct44
Distinct (%)9.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
KISA
105 
한국정보보호진흥원(KISA)
97 
정보보호진흥원(KISA)
67 
한국인터넷진흥원(KISA)
46 
정보통신정책연구원 (KISDI)
22 
Other values (39)
121 

Length

Max length21
Median length20
Mean length11.445415
Min length4

Unique

Unique20 ?
Unique (%)4.4%

Sample

1st row정보보호진흥원(KISA)
2nd row정보보호진흥원(KISA)
3rd row정보보호진흥원(KISA)
4th row한국정보보호센터(KISA)
5th row한국정보보호센터(KISA)

Common Values

ValueCountFrequency (%)
KISA 105
22.9%
한국정보보호진흥원(KISA) 97
21.2%
정보보호진흥원(KISA) 67
14.6%
한국인터넷진흥원(KISA) 46
10.0%
정보통신정책연구원 (KISDI) 22
 
4.8%
한국정보보호진흥원 (KISA) 22
 
4.8%
한국정보보호센터 (KISA) 12
 
2.6%
한국정보보호진흥원 11
 
2.4%
정보없음 9
 
2.0%
한국전산원 (NCA) 7
 
1.5%
Other values (34) 60
13.1%

Length

2023-12-12T22:05:02.254767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
kisa 140
26.3%
한국정보보호진흥원(kisa 98
18.4%
정보보호진흥원(kisa 67
12.6%
한국인터넷진흥원(kisa 46
 
8.6%
한국정보보호진흥원 35
 
6.6%
정보통신정책연구원 24
 
4.5%
kisdi 24
 
4.5%
한국정보보호센터 12
 
2.3%
한국전산원 10
 
1.9%
정보없음 9
 
1.7%
Other values (35) 68
12.8%

담당기관
Text

Distinct156
Distinct (%)34.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-12T22:05:02.571043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length6.5873362
Min length4

Characters and Unicode

Total characters3017
Distinct characters213
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique109 ?
Unique (%)23.8%

Sample

1st row정보없음
2nd row(주)와이즈그램
3rd row정보없음
4th row정보없음
5th row정보없음
ValueCountFrequency (%)
정보없음 224
39.5%
산학협력단 69
 
12.2%
고려대학교 12
 
2.1%
한양대학교 12
 
2.1%
중앙대학교 6
 
1.1%
숭실대학교 5
 
0.9%
성균관대학교 5
 
0.9%
경원대학교 5
 
0.9%
연세대학교 5
 
0.9%
편 4
 
0.7%
Other values (147) 220
38.8%
2023-12-12T22:05:02.994354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 268
 
8.9%
정 256
 
8.5%
학 228
 
7.6%
없 224
 
7.4%
음 224
 
7.4%
대 147
 
4.9%
교 142
 
4.7%
111
 
3.7%
협 94
 
3.1%
산 85
 
2.8%
Other values (203) 1238
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2782
92.2%
Space Separator 111
 
3.7%
Uppercase Letter 42
 
1.4%
Close Punctuation 38
 
1.3%
Open Punctuation 37
 
1.2%
Other Punctuation 2
 
0.1%
Decimal Number 2
 
0.1%
Lowercase Letter 1
 
< 0.1%
Other Symbol 1
 
< 0.1%
Control 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 268
 
9.6%
정 256
 
9.2%
학 228
 
8.2%
없 224
 
8.1%
음 224
 
8.1%
대 147
 
5.3%
교 142
 
5.1%
협 94
 
3.4%
산 85
 
3.1%
단 74
 
2.7%
Other values (178) 1040
37.4%
Uppercase Letter
ValueCountFrequency (%)
I 7
16.7%
S 6
14.3%
N 4
9.5%
C 3
7.1%
G 3
7.1%
T 3
7.1%
D 3
7.1%
R 3
7.1%
F 2
 
4.8%
U 2
 
4.8%
Other values (5) 6
14.3%
Other Punctuation
ValueCountFrequency (%)
/ 1
50.0%
. 1
50.0%
Decimal Number
ValueCountFrequency (%)
3 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 38
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Lowercase Letter
ValueCountFrequency (%)
z 1
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2783
92.2%
Common 191
 
6.3%
Latin 43
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 268
 
9.6%
정 256
 
9.2%
학 228
 
8.2%
없 224
 
8.0%
음 224
 
8.0%
대 147
 
5.3%
교 142
 
5.1%
협 94
 
3.4%
산 85
 
3.1%
단 74
 
2.7%
Other values (179) 1041
37.4%
Latin
ValueCountFrequency (%)
I 7
16.3%
S 6
14.0%
N 4
9.3%
C 3
7.0%
G 3
7.0%
T 3
7.0%
D 3
7.0%
R 3
7.0%
F 2
 
4.7%
U 2
 
4.7%
Other values (6) 7
16.3%
Common
ValueCountFrequency (%)
111
58.1%
) 38
 
19.9%
( 37
 
19.4%
/ 1
 
0.5%
3 1
 
0.5%
. 1
 
0.5%
2 1
 
0.5%
1
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2782
92.2%
ASCII 234
 
7.8%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 268
 
9.6%
정 256
 
9.2%
학 228
 
8.2%
없 224
 
8.1%
음 224
 
8.1%
대 147
 
5.3%
교 142
 
5.1%
협 94
 
3.4%
산 85
 
3.1%
단 74
 
2.7%
Other values (178) 1040
37.4%
ASCII
ValueCountFrequency (%)
111
47.4%
) 38
 
16.2%
( 37
 
15.8%
I 7
 
3.0%
S 6
 
2.6%
N 4
 
1.7%
C 3
 
1.3%
G 3
 
1.3%
T 3
 
1.3%
D 3
 
1.3%
Other values (14) 19
 
8.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%

출판일
Date

Distinct199
Distinct (%)43.4%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum1990-01-26 00:00:00
Maximum2018-04-24 00:00:00
2023-12-12T22:05:03.156713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:05:03.293068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

등록번호
Real number (ℝ)

SKEWED  UNIQUE 

Distinct458
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33126.299
Minimum575
Maximum10000045
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.2 KiB
2023-12-12T22:05:03.446892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum575
5-th percentile1303.05
Q110303.25
median11590.5
Q314079.75
95-th percentile17608.15
Maximum10000045
Range9999470
Interquartile range (IQR)3776.5

Descriptive statistics

Standard deviation466767.66
Coefficient of variation (CV)14.090547
Kurtosis457.90105
Mean33126.299
Median Absolute Deviation (MAD)2223.5
Skewness21.397474
Sum15171845
Variance2.1787205 × 1011
MonotonicityNot monotonic
2023-12-12T22:05:03.621498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
13092 1
 
0.2%
9402 1
 
0.2%
3521 1
 
0.2%
4616 1
 
0.2%
3525 1
 
0.2%
9088 1
 
0.2%
5329 1
 
0.2%
3517 1
 
0.2%
3518 1
 
0.2%
4856 1
 
0.2%
Other values (448) 448
97.8%
ValueCountFrequency (%)
575 1
0.2%
578 1
0.2%
579 1
0.2%
677 1
0.2%
681 1
0.2%
683 1
0.2%
685 1
0.2%
686 1
0.2%
689 1
0.2%
690 1
0.2%
ValueCountFrequency (%)
10000045 1
0.2%
19853 1
0.2%
19851 1
0.2%
19655 1
0.2%
17868 1
0.2%
17739 1
0.2%
17719 1
0.2%
17698 1
0.2%
17663 1
0.2%
17662 1
0.2%

보고서번호
Text

Distinct401
Distinct (%)87.6%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-12T22:05:03.823017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length13.842795
Min length4

Characters and Unicode

Total characters6340
Distinct characters127
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique390 ?
Unique (%)85.2%

Sample

1st rowKISA-RP-2008-0007
2nd rowKISA-RP-2008-0040
3rd rowKISA-RP-2008-0018
4th row정책연구 97-2
5th row정보보호 97-3
ValueCountFrequency (%)
57
 
7.3%
정보없음 48
 
6.2%
연구보고 27
 
3.5%
2006 20
 
2.6%
06-01 15
 
1.9%
nca 9
 
1.2%
04-01 9
 
1.2%
05-01 9
 
1.2%
개인정보보호기획 9
 
1.2%
06-03 9
 
1.2%
Other values (408) 567
72.8%
2023-12-12T22:05:04.144732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1223
19.3%
- 832
 
13.1%
2 334
 
5.3%
321
 
5.1%
1 261
 
4.1%
A 193
 
3.0%
I 183
 
2.9%
9 177
 
2.8%
S 176
 
2.8%
P 173
 
2.7%
Other values (117) 2467
38.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2564
40.4%
Other Letter 1454
22.9%
Uppercase Letter 1145
18.1%
Dash Punctuation 832
 
13.1%
Space Separator 321
 
5.1%
Other Punctuation 14
 
0.2%
Letter Number 4
 
0.1%
Lowercase Letter 4
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 158
 
10.9%
연 141
 
9.7%
구 141
 
9.7%
기 99
 
6.8%
정 91
 
6.3%
고 51
 
3.5%
음 48
 
3.3%
없 48
 
3.3%
호 44
 
3.0%
인 39
 
2.7%
Other values (82) 594
40.9%
Uppercase Letter
ValueCountFrequency (%)
A 193
16.9%
I 183
16.0%
S 176
15.4%
P 173
15.1%
K 170
14.8%
W 154
13.4%
R 35
 
3.1%
T 14
 
1.2%
C 12
 
1.0%
N 10
 
0.9%
Other values (4) 25
 
2.2%
Decimal Number
ValueCountFrequency (%)
0 1223
47.7%
2 334
 
13.0%
1 261
 
10.2%
9 177
 
6.9%
6 126
 
4.9%
3 120
 
4.7%
4 102
 
4.0%
5 87
 
3.4%
7 75
 
2.9%
8 59
 
2.3%
Other Punctuation
ValueCountFrequency (%)
/ 7
50.0%
, 5
35.7%
. 2
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
p 2
50.0%
w 1
25.0%
r 1
25.0%
Letter Number
ValueCountFrequency (%)
Ⅳ 3
75.0%
Ⅲ 1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 832
100.0%
Space Separator
ValueCountFrequency (%)
321
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3733
58.9%
Hangul 1454
 
22.9%
Latin 1153
 
18.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 158
 
10.9%
연 141
 
9.7%
구 141
 
9.7%
기 99
 
6.8%
정 91
 
6.3%
고 51
 
3.5%
음 48
 
3.3%
없 48
 
3.3%
호 44
 
3.0%
인 39
 
2.7%
Other values (82) 594
40.9%
Latin
ValueCountFrequency (%)
A 193
16.7%
I 183
15.9%
S 176
15.3%
P 173
15.0%
K 170
14.7%
W 154
13.4%
R 35
 
3.0%
T 14
 
1.2%
C 12
 
1.0%
N 10
 
0.9%
Other values (9) 33
 
2.9%
Common
ValueCountFrequency (%)
0 1223
32.8%
- 832
22.3%
2 334
 
8.9%
321
 
8.6%
1 261
 
7.0%
9 177
 
4.7%
6 126
 
3.4%
3 120
 
3.2%
4 102
 
2.7%
5 87
 
2.3%
Other values (6) 150
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4882
77.0%
Hangul 1453
 
22.9%
Number Forms 4
 
0.1%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1223
25.1%
- 832
17.0%
2 334
 
6.8%
321
 
6.6%
1 261
 
5.3%
A 193
 
4.0%
I 183
 
3.7%
9 177
 
3.6%
S 176
 
3.6%
P 173
 
3.5%
Other values (23) 1009
20.7%
Hangul
ValueCountFrequency (%)
보 158
 
10.9%
연 141
 
9.7%
구 141
 
9.7%
기 99
 
6.8%
정 91
 
6.3%
고 51
 
3.5%
음 48
 
3.3%
없 48
 
3.3%
호 44
 
3.0%
인 39
 
2.7%
Other values (81) 593
40.8%
Number Forms
ValueCountFrequency (%)
Ⅳ 3
75.0%
Ⅲ 1
 
25.0%
Compat Jamo
ValueCountFrequency (%)
ㄱ 1
100.0%

등록일
Date

Distinct200
Distinct (%)43.7%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
Minimum2005-10-25 00:00:00
Maximum2018-05-17 00:00:00
2023-12-12T22:05:04.282753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:05:04.424646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

보고서분류명
Text

Distinct124
Distinct (%)27.1%
Missing0
Missing (%)0.0%
Memory size3.7 KiB
2023-12-12T22:05:04.694702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length9.8558952
Min length4

Characters and Unicode

Total characters4514
Distinct characters158
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)13.3%

Sample

1st row정보없음
2nd row정보없음
3rd row정보없음
4th row기획평가부／정책지원팀
5th row정책기술지원부/기술분석팀
ValueCountFrequency (%)
정보없음 171
35.1%
개인정보보호지원센터／개인정보보호기획팀 14
 
2.9%
인터넷융합단／융합보호r＆d팀 14
 
2.9%
개인정보보호지원센터／조사분석팀 9
 
1.8%
보안성평가단／산업지원팀 8
 
1.6%
보안성평가단／평가기획팀 8
 
1.6%
it기반보호단／전자인증팀 7
 
1.4%
it기반보호단／암호응용팀 7
 
1.4%
침해예방단／웹보안지원팀 6
 
1.2%
인터넷기반진흥단／ip팀 6
 
1.2%
Other values (123) 237
48.7%
2023-12-12T22:05:05.129286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
보 500
 
11.1%
정 316
 
7.0%
팀 267
 
5.9%
／ 237
 
5.3%
기 214
 
4.7%
호 192
 
4.3%
단 177
 
3.9%
인 173
 
3.8%
음 171
 
3.8%
없 171
 
3.8%
Other values (148) 2096
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4091
90.6%
Other Punctuation 252
 
5.6%
Uppercase Letter 104
 
2.3%
Space Separator 29
 
0.6%
Decimal Number 27
 
0.6%
Dash Punctuation 7
 
0.2%
Lowercase Letter 2
 
< 0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
보 500
 
12.2%
정 316
 
7.7%
팀 267
 
6.5%
기 214
 
5.2%
호 192
 
4.7%
단 177
 
4.3%
인 173
 
4.2%
음 171
 
4.2%
없 171
 
4.2%
터 118
 
2.9%
Other values (122) 1792
43.8%
Uppercase Letter
ValueCountFrequency (%)
I 31
29.8%
T 22
21.2%
D 15
14.4%
R 14
13.5%
P 10
 
9.6%
K 3
 
2.9%
A 3
 
2.9%
C 2
 
1.9%
S 2
 
1.9%
O 1
 
1.0%
Decimal Number
ValueCountFrequency (%)
1 9
33.3%
0 6
22.2%
2 5
18.5%
9 3
 
11.1%
7 2
 
7.4%
5 1
 
3.7%
3 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
／ 237
94.0%
＆ 14
 
5.6%
/ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
u 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4091
90.6%
Common 317
 
7.0%
Latin 106
 
2.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
보 500
 
12.2%
정 316
 
7.7%
팀 267
 
6.5%
기 214
 
5.2%
호 192
 
4.7%
단 177
 
4.3%
인 173
 
4.2%
음 171
 
4.2%
없 171
 
4.2%
터 118
 
2.9%
Other values (122) 1792
43.8%
Common
ValueCountFrequency (%)
／ 237
74.8%
29
 
9.1%
＆ 14
 
4.4%
1 9
 
2.8%
- 7
 
2.2%
0 6
 
1.9%
2 5
 
1.6%
9 3
 
0.9%
7 2
 
0.6%
) 1
 
0.3%
Other values (4) 4
 
1.3%
Latin
ValueCountFrequency (%)
I 31
29.2%
T 22
20.8%
D 15
14.2%
R 14
13.2%
P 10
 
9.4%
K 3
 
2.8%
A 3
 
2.8%
u 2
 
1.9%
C 2
 
1.9%
S 2
 
1.9%
Other values (2) 2
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4091
90.6%
None 251
 
5.6%
ASCII 172
 
3.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
보 500
 
12.2%
정 316
 
7.7%
팀 267
 
6.5%
기 214
 
5.2%
호 192
 
4.7%
단 177
 
4.3%
인 173
 
4.2%
음 171
 
4.2%
없 171
 
4.2%
터 118
 
2.9%
Other values (122) 1792
43.8%
None
ValueCountFrequency (%)
／ 237
94.4%
＆ 14
 
5.6%
ASCII
ValueCountFrequency (%)
I 31
18.0%
29
16.9%
T 22
12.8%
D 15
8.7%
R 14
8.1%
P 10
 
5.8%
1 9
 
5.2%
- 7
 
4.1%
0 6
 
3.5%
2 5
 
2.9%
Other values (14) 24
14.0%

Interactions

2023-12-12T22:05:00.241973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:05:05.222978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류관리조직1등록번호
분류1.0000.2090.000
관리조직10.2091.0000.162
등록번호0.0000.1621.000
2023-12-12T22:05:05.308002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
관리조직1분류
관리조직11.0000.158
분류0.1581.000
2023-12-12T22:05:05.394733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
등록번호분류관리조직1
등록번호1.0000.0000.123
분류0.0001.0000.158
관리조직10.1230.1581.000

Missing values

2023-12-12T22:05:00.408750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:05:00.597222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

분류보고서명관리조직1담당기관출판일등록번호보고서번호등록일보고서분류명
002008 국내 정보보호산업 시장 및 동향조사정보보호진흥원(KISA)정보없음2008-12-31 00:0013092KISA-RP-2008-00072009-03-19 00:00정보없음
10이동단말 환경에서 안전한 위치정보 제공을 위한 보안기술 개발정보보호진흥원(KISA)(주)와이즈그램2008-12-31 00:0013016KISA-RP-2008-00402009-02-11 00:00정보없음
20정보보호제품 품질 평가기준 연구정보보호진흥원(KISA)정보없음2008-12-31 00:0013039KISA-RP-2008-00182009-02-12 00:00정보없음
30정보보호산업 분류 및 실태 조사한국정보보호센터(KISA)정보없음1997-12-20 00:001039정책연구 97-22007-03-06 00:00기획평가부／정책지원팀
40자바 보안 기술분석서한국정보보호센터(KISA)정보없음1997-12-22 00:001141정보보호 97-32007-03-06 00:00정책기술지원부/기술분석팀
50IT기반 미래국가발전전략 연구 총괄보고서정보통신정책연구원(KISDI)정보없음2006-12-01 00:0011843메가트렌드 Ⅳ 06-012007-05-04 00:00정보없음
60u-City 프라이버시 보호방안 연구한국정보보호진흥원정보없음2006-12-31 00:0011690기술정책연구06-012007-03-05 00:00정책개발단／기술정책팀
70EU 개인정보보호지침 준상호주의 이행방안 연구한국정보보호진흥원(KISA)경희대학교2001-11-30 00:007923개인정보연구 01-022007-02-23 00:00전자거래보호단／개인정보보호팀
80WBT(Web Based Training) 기반 평가제출물 작성 e-러닝 시스템 개발한국정보보호진흥원(KISA)성균관대학교2006-12-01 00:0011598평가1연구 06-012007-02-12 00:00보안성평가단／평가1팀
90침해사고 정보수집(TIGS) SW 기능개선한국정보보호진흥원(KISA)(주)엠에스지2006-08-19 00:0011591대응지원연구 06-012007-02-08 00:00인터넷침해사고대응지원센터／대응지원팀
분류보고서명관리조직1담당기관출판일등록번호보고서번호등록일보고서분류명
4481웹사이트 공격정보 수집 모델 연구 최종보고서KISA서울신학대학교 산학협력단2010-08-31 00:0017109KISA-WP-2010-00162010-09-29 00:00침해예방단／웹보안지원팀
4491개인정보침해 신고센터 업무 처리 절차 개선 방안 연구정보없음정보없음2018-02-01 00:0011989KISA-WP-2017-00322018-03-21 16:34정보없음
450117년도 대국민 전자서명 이용실태 조사정보없음정보없음2018-04-24 00:0012072KISA-WP-2017-00342018-04-24 00:00정보없음
4511국내 암호산업 육성을 위한 암호이용 실태조사정보없음정보없음2017-12-15 00:0012129KISA-WP-2017-00282018-05-17 00:00정보없음
4521온라인 트래킹으로부터 이용자 보호를 위한 법제 개선 방안 연구정보없음정보없음2017-08-30 00:0011807KISA-WP-2017-00122018-01-16 14:04정보없음
4531머신러닝 기반 악성코드 분석 알고리즘 적합성 연구한국인터넷진흥원(KISA)서울과학기술대학교산학협력단2017-08-23 00:0011804KISA-WP-2017-00142018-01-16 13:57정보없음
4541플랫폼 중립성 정책개발 기반연구정보없음정보없음2017-12-06 00:0011811KISA-WP-2017-00312018-01-16 14:47정보없음
4551재중국 한국인 개인정보 보호 안내서 개발정보없음정보없음2017-12-18 00:0011968KISA-WP-2017-00362018-04-03 01:25정보없음
4561스마트 교통 취약점 분석 및 대응방안 개발정보없음정보없음2017-11-30 00:0011953KISA-WP-2017-00372018-01-31 13:04정보없음
4571온라인 동영상 광고 현황조사 및 정책 연구정보없음정보없음2017-09-30 00:0010000045KISA-WP-2017-00242018-05-03 13:19정보없음